Object Recognition

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

( Image credit: Tensorflow Object Detection API )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1201–1225 of 2042 papers

Title	Date	Tasks	Status	Hype
Causal importance of orientation selectivity for generalization in image recognition	May 1, 2019	image-classificationImage Classification	CodeCode Available	0
Contextual Recurrent Convolutional Model for Robust Visual Learning	May 1, 2019	Fine-Grained Image ClassificationGeneral Classification	—Unverified	0
Learning what and where to attend with humans in the loop	May 1, 2019	DiagnosticImage Categorization	—Unverified	0
Learning to Find Common Objects Across Few Image Collections	Apr 29, 2019	Few-Shot LearningObject	CodeCode Available	0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers	Apr 25, 2019	3D Object RecognitionGeneral Classification	—Unverified	0
Pointing Novel Objects in Image Captioning	Apr 25, 2019	DecoderImage Captioning	—Unverified	0
Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks	Apr 25, 2019	Data AugmentationObject Recognition	—Unverified	0
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond	Apr 25, 2019	Instance SegmentationObject Detection	CodeCode Available	2
Context-Aware Zero-Shot Learning for Object Recognition	Apr 24, 2019	ObjectObject Recognition	—Unverified	0
PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras	Apr 24, 2019	Dimensionality Reductionfeature selection	—Unverified	0
Facial Expression Recognition Research Based on Deep Learning	Apr 22, 2019	Deep LearningFacial Expression Recognition	CodeCode Available	0
ChoiceNet: CNN learning through choice of multiple feature map representations	Apr 20, 2019	Object RecognitionSemantic Segmentation	—Unverified	0
Context-Aware Zero-Shot Recognition	Apr 19, 2019	Object RecognitionZero-Shot Learning	CodeCode Available	0
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models	Apr 17, 2019	3D Classification3D Object Detection	CodeCode Available	0
People infer recursive visual concepts from just a few examples	Apr 17, 2019	Object Recognition	—Unverified	0
End-to-End Learning of Representations for Asynchronous Event-Based Data	Apr 17, 2019	ClassificationObject Recognition	CodeCode Available	0
Collaboration Analysis Using Deep Learning	Apr 17, 2019	AnatomyDeep Learning	—Unverified	0
Texture image analysis and texture classification methods - A review	Apr 13, 2019	ClassificationDefect Detection	—Unverified	0
Improved training of binary networks for human pose estimation and image recognition	Apr 11, 2019	BinarizationClassification with Binary Neural Network	—Unverified	0
An Application-Specific VLIW Processor with Vector Instruction Set for CNN Acceleration	Apr 10, 2019	Object Recognition	—Unverified	0
On zero-shot recognition of generic objects	Apr 10, 2019	Object RecognitionZero-Shot Learning	CodeCode Available	0
On Learning Density Aware Embeddings	Apr 8, 2019	Face RecognitionMetric Learning	—Unverified	0
Target-Aware Deep Tracking	Apr 3, 2019	ObjectObject Recognition	—Unverified	0
Learning Good Representation via Continuous Attention	Mar 29, 2019	ObjectObject Recognition	—Unverified	0
Local Aggregation for Unsupervised Learning of Visual Embeddings	Mar 29, 2019	ClusteringContrastive Learning	CodeCode Available	0

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All datasets shape bias CIFAR10-DVS N-Caltech 101 ObjectNet (All classes)ObjectNet (ImageNet classes)ObjectNet (ImageNet classes, trained on ImageNet)DVS128 Gesture MECCANO N-CARS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Imagen	shape bias	98.7	—	Unverified
2	Stable Diffusion	shape bias	92.7	—	Unverified
3	Parti	shape bias	91.7	—	Unverified
4	ViT-22B-384	shape bias	86.4	—	Unverified
5	ViT-22B-560	shape bias	83.8	—	Unverified
6	CLIP (ViT-B)	shape bias	79.9	—	Unverified
7	ViT-22B-224	shape bias	78	—	Unverified
8	ResNet-50 (L2 eps 5.0 adv trained)	shape bias	69.5	—	Unverified
9	ResNet-50 (with strong augmentations)	shape bias	62.2	—	Unverified
10	SWSL (ResNeXt-101)	shape bias	49.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.55	—	Unverified
2	SSNN	Accuracy (% )	78.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.62	—	Unverified
2	SSNN	Accuracy (% )	79.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	18.75	—	Unverified
2	yun	Top 5 Accuracy	14.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	DY	Top 5 Accuracy	0.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	AJ2021	Top 5 Accuracy	27.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SSNN	Accuracy (% )	94.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Faster-RCNN	mAP	30.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	96	—	Unverified